Sales Technical Analytics Intern

• Develop data warehouse and data marts that transform raw data into high-performance, structured data models to power analyses & visualization tools for the Sales organization • Build “point-in-time” data models that enable trend analysis such as pipeline flow reporting • Enable Sales Ops users to perform their own ad-hoc analysis by maintaining clean, well-documented, and easy-to-query semantic layers. • Design automated ingestion paths for manual spreadsheet data to ensure they are validated and integrated into the central data environment. • Implement automated data quality checks and monitoring to ensure accuracy across all sales reporting. • Maintain clear documentation of data lineage, business logic, and definitions for all sales-related metrics.

• Engineering Mindset: A preference for "code-first" analytics—moving away from fragile manual processes toward reproducible, tested pipelines. • Expert SQL & Python: Must be comfortable writing complex transformations and using Python for pipeline automation using tools such as Jupyter or Marimo. • Deep understanding of schemas and fact/dimension tables to ensure intuitive self-service for data users • Experience with dbt or similar frameworks that prioritize version-controlled, modular data modeling. • Familiarity with (or eagerness to learn) Customer lifecycles and CRM data structures (e.g. Salesforce) • Uncommonly driven to succeed and maniacally self-initiated; extreme attention to detail • Passion for clean energy and sustainability • Background in a quantitative field such as Mathematics, Economics, Finance, or Engineering is required; MBA experience is preferred